Quick Summary: Group Seasonal Forecasting applies a shared seasonal profile from established items to new or young products with limited sales history. Ensure accurate seasonal forecasts from the start by leveraging group data.
Please note: This feature is only available in the advanced forecasting feature.
When to Use Group Seasonal Forecasting
The existence of group seasonal factors being used to generate a seasonal forecast for an individual item is shown on the Stock Inquiry screen, where the Demand type on the Demand panel will display the words Seasonal group.
The seasonal group profile will be used to generate an item forecast when:
The item is in a group that is clearly seasonal, and
Either the item’s limited sales history means that seasonality cannot be detected, or
The item has sufficient history, but the seasonality thresholds for a self-generated seasonal forecast have not been met.
How the Seasonal Profile is Created
The group seasonal profile, which is used as the "donor" for the forecast, is created by:
Aggregating sales history of all items in the group.
Generating a forecast based on the aggregated sales.
Identifying the resultant forecast profile as seasonal.
How the Item Forecast is Generated
Once the group seasonal profile is created, the individual item forecast is generated in a two-step process:
The app forecasts the individual item to get a forecast "level" (a baseline demand).
The seasonal forecast profile from the group is then applied to the item’s baseline "level" to create the final seasonal forecast.
The Group Seasonal Profile Graphic
By clicking on the words Seasonal group in the Demand panel, you can view the graphic that provides a detailed overview of the profile being used.
This graphic displays:
The selected group: The name of the group, for example, Construction: Description for Construction.
Charts: Multiple years of sales history and the forecast for this group.
Stats: The row underneath the chart includes:
Year-on-Year: A stacked view of seasonal profiles across multiple years.
Comparison: Shows any sales growth or decline trends for the group.
Item count: The number of items included in this group.
Age Distribution: A view of how items fall between the maximum and minimum age.
Avg, Max, and Min Age: The average age, oldest item, and youngest item in the group.
⚠️ Watchouts
Incorrect Grouping: The most significant risk is grouping items with dissimilar seasonal patterns. An incorrect grouping will distort the seasonal curve and lead to inaccurate forecasts for all recipient items.
Anomalies are Inherited: If the donor group's history contains a major anomaly (e.g., a stockout or a one-time promotion), this will affect the seasonal curve and be passed on to the recipient items.
💡 Tips
Clean the Donor History: Before setting up a seasonal group, use the Event Correction feature to clean the donor items' historical sales data of any anomalies. This ensures the seasonal curve is based on the most accurate data possible.
Keep Groups Small and Targeted: For best results, create small, highly targeted seasonal groups of items that are truly similar. For example, group "high-end red wines" together rather than "all wines."
Annual Review: Review your seasonal group memberships annually before key seasonal events. Products change, and a new product's initial sales pattern may have matured into its own unique trend.
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